We evaluate our algorithm together with several state-of-the-art algorithms on two adaptation tasks, e.g., SYNTHIA [1]} \(\rightarrow \)  Cityscapes [2]} and GTA5 [3]} \(\rightarrow \)  Cityscapes. Cityscapes is a real-world dataset with \(5,000\)  street scenes which are divided into a training set with \(2,975\)  images, a validation set with 500 images and a testing set with \(1,525\)  images. We use Cityscapes as the target domain. GTA5 contains \(24,966\)  high-resolution images, automatically annotated into 19 classes. The dataset is rendered from a modern computer game, Grand Theft Auto V, whose labels are fully compatible with Cityscapes. SYNTHIA contains \(9,400\)  synthetic images compatible with the Cityscapes annotated classes. We use SYNTHIA or GTA5 as the source domain in the evaluation.
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